Continuous-Control-Set Model-Free Predictive Control Using Time-Series Subspace for PMSM Drives

Recently, data analysis is used in model-free predictive control to mitigate the effects of parameter mismatches in parametric models. However, the finite-control-set (FCS) type cannot fully satisfy high-quality requirements due to the variable switching frequency, and it is necessary to consider th...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2024-07, Vol.71 (7), p.1-11
Main Authors: Wang, Fengxiang, Wei, Yao, Young, Hector, Ke, Dongliang, Huang, Dongxiao, Rodriguez, Jose
Format: Article
Language:English
Subjects:
Algorithms
Continuous-control-set (CCS) type
Control algorithms
Control theory
Data analysis
Data models
Estimation
Mathematical models
model-free predictive control
Observers
Parameters
permanent magnet synchronous motor (PMSM)
Permanent magnets
Physical properties
Prediction algorithms
Predictive control
Predictive models
Stability analysis
Stators
Subspaces
Synchronous motors
Time series
time-series subspace
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Summary:Recently, data analysis is used in model-free predictive control to mitigate the effects of parameter mismatches in parametric models. However, the finite-control-set (FCS) type cannot fully satisfy high-quality requirements due to the variable switching frequency, and it is necessary to consider the continuous-control-set (CCS) type to achieve better control performances. Nevertheless, the use of conventional time series structures in CCS model-free predictive control algorithms poses a challenge due to the complex design of control laws. To address this issue, this article proposes a CCS model-free predictive control based on a time-series subspace, which is then applied to a permanent magnet synchronous motor (PMSM) driving system. This method constructs a time-series subspace model from data and creates a suitable control law using the recursive least squares algorithm and Lagrange method without any time-varying physical parameters, to predict the future behavior of the stator voltage. The stability of the proposed method is analyzed through Bode diagrams and zero/pole maps under different conditions. A complete set of experiments proves the feasibility and advantages including improved current quality, tracking performances, and system noises compared to the conventional control strategies
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2023.3310017